Introduction. One of the health problems at the present stage is the prevalence of chronic diseases, the genesis of which is predominantly multifactorial in nature, the prevalence of comorbidity. All this makes it difficult to diagnose, treat, prevent and predict the main types of pathology. Target. The aim of this study was to develop a computer program for a comprehensive assessment of cardiovascular risk using several predictive methods. Materials and methods. 150 patients with bronchial asthma were examined, which were divided into 3 groups depending on the ratio of the onset time of asthma to obesity: "Obesity + asthma" (Group 1), "Asthma + Obesity" (Group 2), "patients with asthma and normal body weight" (group 3). The comparison group consisted of 30 relatively healthy volunteers. The following were studied: the degree of obesity and asthma, respiratory function parameters, lipid profile, insulin metabolism, levels of adipokines, apoptotic cells in the blood, echocardiography was performed. Then, to develop algorithms, classification models were built using the mathematical apparatus of logistic regression equations, classification trees and artificial neural networks in the IBM SPSS Statistics v.19. Results. Among the resulting logistic regression equations, the most optimal equation was obtained using the inverse stepwise method at step 21 using the coefficients: asthma severity and control level, waist and hip circumference, epicardial adipose tissue thickness, total cholesterol, triglycerides, very low density lipoproteins, interleukins 2 and 17, insulin resistance, as well as the value of the mass of the myocardium of the left ventricle. Among the obtained classification trees, the most optimal one was obtained using the CHAID construction method, which includes 13 nodes. Among artificial neural networks, the optimal one had as input features: body mass index, degree of asthma, proportion of cells in apoptosis, adiponectin, leptin, low-density lipoproteins and interleukin-17 in blood plasma, and glycated hemoglobin. These algorithms have demonstrated high values of sensitivity, specificity, and accuracy. Discussions. In the last decade, the mutual influence of asthma and cardiovascular pathology has been noted. It should be noted that asthma is not just a local inflammatory disease, but rather a systemic inflammatory pathology with high levels of inflammatory markers that mediate many of both the respiratory and cardiac targets of asthma. There is no doubt that obesity is one of the key links in the cardiometabolic continuum. The basis of the association between obesity and cardiovascular pathology is insulin resistance, an imbalance in the adipokine and lipid profile. Conclusion. To implement the concept of cardiovascular risk management, we created the program "Intelligent system of doctor-patient interaction in bronchial asthma and comorbid pathology".